期刊
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 19, 期 7, 页码 4617-4631出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2020.2985686
关键词
Downlink; Array signal processing; Uplink; MIMO communication; Training; Channel estimation; Approximation algorithms; Massive MIMO; FDD; statistical beamforming; spatial reciprocity
资金
- Research Grants Council of Hong Kong [14208017]
- National Key Research and Development Program of China [2018YFB1801105]
- 111 Project of China [B20064]
In this paper, we study the beamforming design problem in frequency-division duplexing (FDD) downlink massive MIMO systems, where instantaneous channel state information (CSI) is assumed to be unavailable at the base station (BS). We propose to extract the information of the angle-of-departures (AoDs) and the corresponding large-scale fading coefficients (a.k.a. spatial information) of the downlink channel from the uplink channel estimation procedure, based on which a novel downlink beamforming design is presented. By separating the subpaths for different users based on the spatial information and the hidden sparsity of the physical channel, we construct near-orthogonal virtual channels in the beamforming design. Furthermore, we derive a sum-rate expression and its approximations for the proposed system. Based on these closed-form rate expressions, we develop two low-complexity beam selection schemes and carry out asymptotic analysis to provide valuable insights on the system design. Numerical results demonstrate a significant performance improvement of our proposed algorithm over the state-of-the-art beamforming approach.
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